Systems | Development | Analytics | API | Testing

Product lifecycle management is all about the dynamics between requirements and their fulfilment (e.g., the ability to test and prove that a requirement is fully covered, as defined during the product planning phase). Understanding this relationship, and respecting it unconditionally, allows great products to achieve world-class quality and stability. For the majority of products, the combination of people, processes, and technology is triggering different forms of changes to the original plan.

Data integration has been around for decades in some form or fashion, as organizations are always looking for ways to combine their enterprise data and collect it in a centralized location. The most commonly used and dominant type of data integration is ETL (extract, transform, load). ETL first extracts data from one or more source systems, transforms it as necessary, and then loads it into a target warehouse or data lake.

Most organizations today have some form of digital transformation strategy in the works. But a large share of these projects fail. Why is this? IT specialists will tell you that apart from misalignment between the goals of IT and business leadership, the main obstacle to a successful digital transformation is the adherence to obsolete data silos.

From Silicon Valley startups to established corporations, more and more companies are shifting to a composable enterprise architecture. And it is easy to see why. The world of business technology is growing fast and in unpredictable ways. Businesses need to stay competitive by keeping pace with — or better yet, ahead of — emerging tech. Composable enterprises allow for this flexibility by establishing the groundwork for integrating new applications and functionalities.

What’s the fastest and easiest path towards powerful cloud-native analytics that are secure and cost-efficient? In our humble opinion, we believe that’s Cloudera Data Platform (CDP). And sure, we’re a little biased—but only because we’ve seen firsthand how CDP helps our customers realize the full benefits of public cloud.

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. It’s a pie-in-the-sky statement that sounds great, right? And while you’d be forgiven for thinking that it might sound too good to be true, operational ML is, in fact, achievable and sustainable. You can get the very kind of ML you need to increase revenue and lower costs. To help teams work smarter and do things faster.

Trying to integrate your marketing data sources? Here are the fundamental differences between Fivetran and Supermetrics as marketing ETL tools.

Wondering what are the top SEO Chrome extensions the experts use for ranking, technical and on-page SEO, and more? We’ve got the list for you.

DevOps merges operational and development teams to boost the speed of software development and ensure that the final product is delivered as clean and consistent as possible. Ultimately, DevOps allows teams to increase product quality and speed of delivery in even the most highly competitive environments. The idea of weaving together disparate teams to accelerate development might appeal to many organizations, but some common challenges may come up before implementing a DevOps environment.

This is the story of how Appian helped organizations worldwide get thousands of people back to work during the worst global pandemic in over a century, safely and legally. The Appian Workforce Safety Solution COVID-19 threw people worldwide into what seemed like a black hole of chaos. As infection rates rapidly grew, and related concerns grew even faster, communities struggled to respond.